Muscle radiodensity and mortality in patients with colorectal cancer
Bibliographic record
Abstract
BACKGROUND: Low skeletal muscle radiodensity (SMD) is related to higher mortality in several cancers, but the association with colorectal cancer (CRC) prognosis is unclear. METHODS: This observational study included 3262 men and women from the Kaiser Permanente Northern California population diagnosed between 2006 and 2011 with AJCC stages I to III CRC. The authors evaluated hazard ratios (HRs) of low SMD for all-cause and CRC-specific mortality, assessed by computed tomography using optimal stratification, compared with patients with normal SMD. They also evaluated the cross-classification of categories of low versus normal SMD and muscle mass (MM) with outcomes. RESULTS: The median follow-up was 6.9 years. Optimal stratification cutpoints for SMD were 32.5 in women and 35.5 in men. In multivariate-adjusted analyses, among patients with CRC, those with low SMD demonstrated higher overall (HR, 1.61; 95% confidence interval [95% CI], 1.36-1.90) and CRC-specific (HR, 1.74; 95% CI, 1.38-2.21) mortality when compared with those with normal SMD levels. Patients with low SMD and low MM (ie, sarcopenia) were found to have the highest overall (HR, 2.02; 95% CI, 1.65-2.47) and CRC-specific (HR, 2.54; 95% CI, 1.91-3.37) mortality rates. CONCLUSIONS: In patients with CRC, those with low SMD were found to have elevated risks of disease-specific and overall mortality, independent of MM or adiposity. Clinical practice should incorporate body composition measures into the evaluation of the health status of patients with CRC. Cancer 2018;124:3008-15. © 2018 American Cancer Society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".